N. L. Abraham

Multimodel estimates of atmospheric lifetimes of long‐lived ozone‐depleting substances: Present and future

We have diagnosed the lifetimes of long-lived source gases emitted at the surface and removed in the stratosphere using six three-dimensional chemistry-climate models and a two-dimensional model. The models all used the same standard photochemical data. We investigate the effect of different definitions of lifetimes, including running the models with both mixing ratio (MBC) and flux (FBC) boundary conditions. Within the same model, the lifetimes diagnosed by different methods agree very well. Using FBCs versus MBCs leads to a different tracer burden as the implied lifetime contained in the MBC value does not necessarily match a models own calculated lifetime. In general, there are much larger differences in the lifetimes calculated by different models, the main causes of which are variations in the modeled rates of ascent and horizontal mixing in the tropical midlower stratosphere. The model runs have been used to compute instantaneous and steady state lifetimes. For chlorofluorocarbons (CFCs) their atmospheric distribution was far from steady state in their growth phase through to the 1980s, and the diagnosed instantaneous lifetime is accordingly much longer. Following the cessation of emissions, the resulting decay of CFCs is much closer to steady state. For 2100 conditions the model circulation speeds generally increase, but a thicker ozone layer due to recovery and climate change reduces photolysis rates. These effects compensate so the net impact on modeled lifetimes is small. For future assessments of stratospheric ozone, use of FBCs would allow a consistent balance between rate of CFC removal and model circulation rate.

Modelling future changes to the stratospheric source gas injection of biogenic bromocarbons

Simulations with a chemistry-climate model (CCM) show a future increase in the stratospheric source gas injection (SGI) of biogenic very short-lived substances (VSLS). For 2000, the modelled SGI of bromine from VSLS is similar to 1.7 parts per trillion (pptv) and largest over the tropical West Pacific. For 2100, this increases to similar to 2.0 and similar to 2.7 pptv when the model is forced with Intergovernmental Panel on Climate Change (IPCC) representative concentration pathways (RCPs) 4.5 and 8.5. The increase is largely due to stronger tropical deep convection transporting more CHBr3 to the lower stratosphere. For CH2Br2, CHBr2Cl, CH2BrCl and CHBrCl2, changes to primary oxidant OH determines their SGI contribution. Under RCP 4.5 (moderate warming), OH increases in a warmer, more humid troposphere. Under RCP 8.5 (extreme warming) OH decreases significantly due to a large methane increase, allowing greater SGI of bromine from these VSLS. Potentially enhanced VSLS emissions in the future would further increase these estimates. Citation: Hossaini, R., et al. (2012), Modelling future changes to the stratospheric source gas injection of biogenic bromocarbons, Geophys. Res. Lett., 39, L20813, doi:10.1029/2012GL053401.

Using a Virtual Machine environment for developing, testing, and training for the UM-UKCA Composition-Climate Model, using Unified Model version 10.9 and above

The Met Office Unified Model (UM) is a state-ofthe-art weather and climate model that is used operationally worldwide. UKCA is the chemistry and aerosol sub model of the UM that enables interactive composition and physical atmosphere interactions, but which adds an additional 120 000 lines of code to the model. Ensuring that the UM code and UM-UKCA (the UM running with interactive chemistry and aerosols) is well tested is thus essential. While a comprehensive test harness is in place at the Met Office and partner sites to aid in development, this is not available to many UM users. Recently, the Met Office have made available a virtual machine environment that can be used to run the UM on a desktop or laptop PC. Here we describe the development of a UM-UKCA configuration that is able to run within this virtual machine while only needing 6 GB of memory, before discussing the applications of this system for model development, testing, and training. Copyright statement. The works published in this journal are distributed under the Creative Commons Attribution 4.0 License. This license does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 4.0 License and the OGL are interoperable and do not conflict with, reduce, or limit each other.